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Villiers-le-Bel, France

Boudou-Rouquette P.,Center for Research on Angiogenesis Inhibitors | Ropert S.,Center for Research on Angiogenesis Inhibitors | Mir O.,Center for Research on Angiogenesis Inhibitors | Coriat R.,Center for Research on Angiogenesis Inhibitors | And 8 more authors.
Oncologist | Year: 2012

Background. Sorafenib displays major interpatient phar- macokinetic variability. It is unknown whether the phar- macokinetics of sorafenib influence its toxicity. Methods. We analyzed the severity and kinetics of sorafenib-induced toxicities in unselected consecutive pa- tients with cancer, as well as their relationship with biolog- ical, clinical, and pharmacokinetic parameters. Toxicity was recorded bimonthly. Sorafenib plasma concentrations were assessed by liquid chromatography. Results. For 83 patients (median age, 62 years; range, 21-84 years), median sorafenib 12-hour area under the curve (AUC0-12) was 52.8 mg · h/L (range: 11.8-199.6). A total of 51 patients (61%) experienced grade 3-4 toxicities, including hand-foot skin reactions (23%), asthenia (18%), and diarrhea (11%). Sorafenib AUC0-12preceding grade 3-4 toxicities was significantly higher than that observed in the remaining population (61.9 mg · h/L vs. 53 mg · h/L). In 25 patients treated with fixed doses of sorafenib for the first 4 months, median dose-normalized AUC0-12 on day 120 was significantly lower than on day 15 (63 vs. 102 mg · h/L). The incidence of hypertension and hand-foot skin re- actions significantly decreased over time. Conclusion. Sorafenib AUC0-12decreases over time, similarly to the incidence of hypertension and hand-foot skin reactions. Monitoring of sorafenib plasma concentra- tions may help to prevent acute severe toxicities and detect patients with suboptimal exposure at disease progression. © AlphaMed Press.

Sulahian A.,University Paris Diderot | Porcher R.,University Paris Diderot | Bergeron A.,University Paris Diderot | Touratier S.,Pharmacie | And 4 more authors.
Journal of Clinical Microbiology | Year: 2014

This study was undertaken to examine the performance of the Fungitell-glucan (BG) assay, to compare it with that of the galactomannan (GM) test for the diagnosis of invasive aspergillosis (IA) in patients with hematological malignancies, and to examine the rates of false-positive BG and GM test results due to β-lactam antibiotics among sera of patients with Gram-positive or Gram-negative bacteremia and selected sera with false-positive results from the GM test. Serum samples from 105 patients with proven (n=14) or probable (n=91) IA, 97 hematology patients at risk for invasive fungal infections, 50 healthy blood donors, and 60 patients with bacteremia were used to study the sensitivities and specificities of the assays. The GM test was more specific than the BG assay (97% versus 82%, respectively; P<0.0001) and the BG assay was more sensitive than the GM test (81% versus 49%, respectively; P<0.0001) for IA diagnosis. The study of 49 separate batches of β-lactam antibiotics showed high and very similar rates of false-positive results for the GM and BG assays (29 and 33%, respectively; P=0.82) but with an almost complete lack of concordance between the 2 assays. For patients with bacteremia, the rate of false-positive results was much higher with the BG test than with the GM test (37% versus 2%, respectively; P<0.0001), with no significant difference between Gram-positive and Gram-negative bacteremia. In conclusion, the BG test may be useful for the diagnosis of IA because of its high sensitivity in comparison with the GM test, but the overall benefit of this assay remains limited because of its inadequate specificity and its cost. Copyright © 2014, American Society for Microbiology. All Rights Reserved.

Champion S.,Reanimation Medicale et Toxicologique | Lapidus N.,Biostatistiques | Cherie G.,Pharmacie des batignoles | Spagnoli V.,Cardiologie | And 2 more authors.
Cardiovascular Therapeutics | Year: 2014

Background: Pentoxifylline possess antiinflammatory and rheological properties and has been tested in heart failure (HF). Methods: A comprehensive search was performed from 1980 until July 2013 in PubMed, to identify randomized controlled trials evaluating pentoxifylline versus placebo in HF, to determine impact on mortality. Search strategy is as follows: "Pentoxifylline" AND "heart" AND "trial". Study selection of six randomized controlled trials evaluating mortality as outcome. Then, we conducted a meta-analysis of randomized controlled trials versus placebo in HF. Determination of Mantel-Haenszel fixed effect and random-effect pooled odds ratios for all-cause mortality and corresponding 95% confidence intervals. Results: Data from a total of 221 patients with LVEF ≤40% from six randomized controlled trials were included in this analysis. Pentoxifylline 1200 mg per day was administered during 6 months, except in one study (administered during 1 month for severe acute HF). The use of pentoxifylline was not significantly associated with a reduction in mortality in HF in individual studies. The pooled data including 221 patients showed a nearly fourfold reduction in mortality (5.4% vs. 18.3%; OR 0.29; CI 0.12-0.74; P < 0.01) with homogenous results (I2 0%). Conclusion: A meta-analysis evaluating pentoxifylline versus placebo in HF suggested a significant nearly fourfold decrease in all-cause mortality in the pentoxifylline group. © 2014 John Wiley & Sons Ltd.

Tod M.,Pharmacie | Tod M.,University of Lyon | Goutelle S.,University of Lyon | Gagnieu M.C.,Laboratoire Of Pharmacologie
Clinical Pharmacology and Therapeutics | Year: 2011

We propose a framework to enable quantitative prediction of the impact of CYP2D6 polymorphisms on drug exposure. It relies mostly on in vivo data and uses two characteristic parameters: one for the drug and the other for the genotype. The metric of interest is the ratio of drug area under the curve (AUC) in patients with mutant genotype to the AUC in patients with wild-type genotype. Any combination of alleles, as well as duplications, may be accommodated in the framework. Estimates of the characteristic parameters were obtained by orthogonal regression for 40 drugs and five classes of genotypes, respectively, including poor, intermediate, and ultrarapid metabolizers (PMs, IMs, and UMs). The mean prediction error of AUC ratios was 0.05, and the mean prediction absolute error was 0.20. An external validation was also carried out. The model may be used to predict the variations in exposure induced by all drug-genotype combinations. An application of this model to a rare combination of alleles (410) is described. © 2011 American Society for clinical Pharmacology and therapeutics.

Verstuyft C.,Service de Genetique Moleculaire | Verstuyft C.,University Paris - Sud | Delavenne X.,Jean Monnet University | Rousseau A.,Unite de Recherche Clinique Paris Est | And 7 more authors.
Clinical Pharmacokinetics | Year: 2012

Background and Objective: Vitamin K epoxide reductase complex, subunit 1 (VKORC1) and cytochrome P450 2C9 (CYP2C9) polymorphisms are taken into account when predicting a safe oral dose of coumarin anticoagulant therapy, but little is known about the effects of genetic predictors on the response to fluindione and acenocoumarol. The aims of this study were to characterize the relationship between fluindione and acenocoumarol concentrations and the international normalized ratio (INR) response, and to identify genetic predictors that are important for dose individualization. Methods: Fluindione concentrations, S-and R-acenocoumarol concentrations, the INR and genotype data from healthy subjects were used to develop a population pharmacokinetic-pharmacodynamic model in Monolix software. Twenty-four White healthy subjects were enrolled in the pharmacogenetic study. The study was an open-label, randomized, two-period cross-over study. The subjects received two doses of an oral anticoagulant: 20 mg of fluindione (period A) or 4mg of acenocoumarol (period B). The pharmacokinetics and pharmacodynamics were studied from day 2 to day 3. Results:Atwo-compartmentmodelwith a first-order inputmodel was selected as the basemodel for the twodrugs. The pharmacodynamic response was best described by an indirect action model with S-acenocoumarol concentrations and fluindione concentrations as the only exposure predictors of the INR response. Three covariates (CYP2C9 genotype, VKORC1 genotype and body weight) were identified as important predictors for the pharmacokinetic-pharmacodynamic model of S-acenocoumarol, and four covariates (CYP2C9 genotype, VKORC1 genotype, CYP1A2 phenotype and body weight) were identified as predictors for the pharmacokinetic-pharmacodynamicmodel of fluindione. Because some previous studies have shown a dose-response relationship between smoking exposure and the CYP1A2 phenotype, it was also noted that smokers have greater CYP1A2 activity. Conclusion: During initiation of therapy, CYP2C9 and VKORC1 genetic polymorphisms are important predictors of fluindione and acenocoumarol pharmacokinetic-pharmacodynamic responses. Our result suggests that it is important to take the CYP1A2 phenotype into account to improve individualization of fluindione therapy, in addition to genetic factors.

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